stroke width transform (SWT) text detection algorithm on the Nokia N900 from "Detecting text in natural scenes with stroke width transform" presented by Epshtein, B., Ofek, E., and Wexler, Y. at CVPR ’10. The purpose of the algorithm is to segment out likely regions of text from an image, in order to clean the input of an optical character recognition algorithm. We followed the general framework mentioned in the paper, but deviated from it in several places. Overall, our implementation is not as successful as mentioned in the CVPR paper as we encountered several problems that are not mentioned in that paper. Motivational Example

Steps behind the work-flow :

Take the Image, compute the edge map ( Canny Filter ) and then Apply the Stroke Width Transform.

The right hand side of the image describes the second part of the code where we find the letter candidates, do extra filtering , text line aggregation , word detection and masking.

Downloads :1. Our writeup for the above work is Here2.Example Images from our algorithm are zipped here . 3. Code ( Written in C++ , Runs both on Mobile and PC ) is being posted here because lots of people have emailed/called us requesting the code for SWT transform. Please send an email to ( dce.saurav@gmail.com / arp86@cornell.edu ) to acknowledge us the download of code. You can now download the code by clicking here .

NEW : July, 2012Since we've been getting so many emails about the text detection code, Andrew has released a simpler version of the text detection code with fewer
dependencies, no phone stuff, and a clearer readme on Github link .

References : Original CVPR Paper "Detecting text in natural scenes with stroke width transform" is here .Video lecture of the Main Microsoft Research Guys is here.